Pediatric Diabetes最新文献

Objective: This study sought to examine the reliability and validity of a novel pediatric type 1 diabetes knowledge assessment (KAT-1) designed for children, adolescents, young adults and their parents/guardians. The instrument was designed to be integrated into the clinic workflow to obtain objective data electronically.

Research design and methods: KAT-1 was developed by a multidisciplinary team and includes 11 independent topical subscales. Forty children/caregivers participated in a pilot study; their feedback was used to improve item clarity and readability. Subsequently, a validation study was performed in 200 participants (100 children/adolescents/young adults with type 1 diabetes ages 11-21 years and 100 parents/guardians of children with type 1 diabetes ages 1-15 years) to examine correlations between the KAT-1 scores and Revised Diabetes Knowledge Test (DKT2) scores and HbA1c. An item analysis was conducted to determine internal consistency and reliability; topical subscales were evaluated using Cronbach's alpha.

Results: Total KAT-1 scores were positively correlated with DKT2 scores r = 0.674, p < 0.001, and negatively correlated with HbA1c, r = -0.3, p < 0.001. All KAT-1 subscales were positively and significantly correlated with one another and with total KAT-1 score. Internal consistency of total KAT-1 score was strong (Cronbach's α = 0.938, mean score 84.6, SD = 16.1) and 9 of 11 independent topical subscales demonstrated strong internal consistency. Completion time for subscales was <5 min.

Conclusions: KAT-1 is a valid instrument to assess type 1 diabetes knowledge. The instrument's short topical subscales can be used to objectively assess specific knowledge and individualize diabetes education. KAT-1 has been integrated into our electronic health record (EPIC) and is available online at no cost.

Background: Diabetic ketoacidosis (DKA) is a common, life-threatening complication of type 1 diabetes (T1D) characterized by unregulated ketogenesis caused by relative or absolute insulin deficiency. DKA management requires frequent biochemical monitoring. Plasma ß-hydroxybutyrate (BOHB) has not been included in traditional definitions of DKA resolution.

Objective: The aim of this study was to determine a cut-point level of BOHB to define DKA resolution in patients with T1D treated with intravenous (IV) insulin.

Subjects: We identified patients with T1D receiving IV insulin for DKA treatment at a quaternary children's hospital from January 1, 2017 through December 31, 2020 who had plasma measurements of BOHB after DKA onset and whose DKA resolved by traditional laboratory criteria (venous pH (vpH) ≥ 7.3, serum bicarbonate (HCO₃ ) ≥ 15 mmol/L, and/or anion gap (AG) ≤ 14 mmol/L).

Methods: Associations between plasma BOHB and vpH, HCO₃ , and AG were evaluated via scatterplots. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate BOHB cut-points to predict DKA resolution.

Results: We analyzed 403 patients with 471 unique encounters. Plasma BOHB showed the most robust relationship with AG. The ROC curve comparing plasma BOHB to the accepted definition of DKA resolution, AG ≤14 mmol/L, had an AUC of 0.92. A BOHB value of <1.5 mmol/L had a sensitivity of 83% and specificity of 87%; this cut-point correctly classified 86% of the observations.

Conclusions: A plasma BOHB value of <1.5 mmol/L can be used to define resolution of DKA.

The Janus face metaphor approach highlights that a technology may simultaneously have two opposite faces or properties with unforeseen paradoxes within human-technology interaction. Suboptimal acceptance and clinical outcomes are sometimes seen in adolescents who use diabetes-related technologies. A traditional linear techno-determinist model of technology use would ascribe these unintended outcomes to suboptimal technology, suboptimal patient behavior, or suboptimal outcome measures. This paradigm has demonstratively not been successful at universally improving clinical outcomes over the last two decades. Alternatively, the Janus face metaphor moves away from a linear techno-determinist model and focuses on the dynamic interaction of the human condition and technology. Specifically, it can be used to understand variance in adoption or successful use of diabetes-related technology and to retrospectively understand suboptimal outcomes. The Janus face metaphor also allows for a prospective exploration of potential impacts of diabetes-related technology by patients, families, and their doctors so as to anticipate and minimize potential subsequent tensions.

Introduction: Survival from type 1 diabetes Mellitus is low in lower-income countries with underdeveloped health systems. Support programs from partners like life for a child (LFAC) and changing diabetes in children (CDiC) were implemented in Tanzania in 2005 to provide diabetes care to children and youth. No evaluation of survival has been done since their implementation.

Objective: To assess the survival of children and youth living with diabetes mellitus (CYLDM) in Tanzania.

Methods: A retrospective data collection from 39 clinics of CYLDM was done by extracting data from the diabetes registry between 1991 and 2019. Three cohort were analyzed (1) Cohort 1991-2004 (pre-implementation), (2) Cohort 2005-2010 (during implementation), and (3) 2011-2019 (after the implementation of LFAC/CDiC). Data were analyzed using STATA-version 14.

Results: A total of 3822 data of CYLDM were extracted, mean age at diagnosis was 13.8 (±5) years. Approximately fifty-one percent (50.8%) were male. The total observation time was 28 years, and the Median duration of diabetes of 5 (IQR2, 8) years. Total death was 95 (3%), with a mean age at death of 17.7 (SD 4.7) years. The last cohort (2011-2019) had more diagnosis 2353 (72.7%), as compared to the <2005 cohort with only 163(5%). The survival improved from 59% before 2005 to 69% in the last cohort (2011-2019).

Conclusion: The implemented programs have facilitated the diagnosis and retention of CYLDM in the health care system. In doing so, it has also increased the survival probability in Tanzania compared to the early 90s.